A new management tactic for Eucryptorrhynchus scrobiculatus (Coleoptera: Curculionidae) based on factors influencing the weevil population density

2021 ◽  
Author(s):  
Kailang Yang ◽  
Junbao Wen
Keyword(s):  
Population Density ◽  
Factors Influencing

scholarly journals 1605. Temperature Modulates the Rate of Increase of Antibiotic Resistance Across Europe

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S585-S586
Author(s):  
Sarah McGough ◽  
Derek MacFadden ◽  
Mohammad Hattab ◽  
Kare Molbak ◽  
Mauricio Santillana
Keyword(s):  
Public Health ◽  
Antibiotic Resistance ◽  
Population Density ◽  
Antibiotic Consumption ◽  
Human Populations ◽  
Ambient Temperatures ◽  
E Coli ◽  
Factors Influencing ◽  
Rate Of Increase ◽  
Public Health Threat

Abstract Background Widely recognized as a major public health threat globally, the rapid increase of antibiotic resistance in bacteria could soon render our most effective method to combat infections obsolete. Factors influencing the burden of resistance in human populations remain poorly described, though temperature is known to play an important role in mechanisms of bacterial growth and transmission. Methods Here, we present the first evidence that ambient temperatures may modulate the rate of increase of antibiotic resistance across Europe. Using a comprehensive dataset containing information across 28 countries, for 17 years (2000–2016), 3 common bacterial pathogens, and 4 antibiotic classes collectively representing over 4 million tested isolates, we show that antibiotic resistance has increased more rapidly in warmer regions over a period of nearly 2 decades. Results Specifically, we show that European countries with 10°C warmer ambient temperatures have experienced more rapid increases in antibiotic resistance to E. coli and K. pneumoniae over the 17-year period, ranging between 0.33%/year (95% CI 0.2, 0.5) and 1.2%/year (0.4, 1.9), even after accounting for recognized drivers of resistance including antibiotic consumption and population density. We found a decreasing relationship for S. aureus and methicillin of -0.4%/year (95% CI −0.7, 0.0), reflecting widespread declines in MRSA across Europe over the study period. Conclusion Our findings suggest that rising temperatures globally may hasten the spread of resistance and complicate efforts to mitigate it. Disclosures All authors: No reported disclosures.

scholarly journals Factors Influencing Modern Wildfire Occurrence in the Mark Twain National Forest, Missouri

2007 ◽  
Vol 31 (2) ◽  
pp. 73-84 ◽  
Author(s):  
Kimberley D. Brosofske ◽  
David T. Cleland ◽  
Sari C. Saunders
Keyword(s):  
Logistic Regression ◽  
Population Density ◽  
Mark Twain ◽  
Easy Access ◽  
Anthropogenic Factors ◽  
National Forest ◽  
Fire Occurrence ◽  
Fire Size ◽  
Wildfire Occurrence ◽  
Factors Influencing

Abstract Understanding relative influences of ecological and anthropogenic factors on wildfire occurrence can assist decisionmakers in allocating fire management resources. We examined the influences of ecological and anthropogenic variables on probability of modern fire occurrence in the Mark Twain National Forest (MTNF), Missouri, using classification and regression tree (CART) and logistic regression analyses. Models were developed for five classes of fire size. Although CART distinguished some effects of fire size on results, logistic regression indicated a single model developed for all fires was sufficient for predictions. Ecological subsection was a dominating influence on fire occurrence for final CART and logistic models, highlighting the potential usefulness of ecosystem classification as a framework for considering factors influencing modern wildfires. Other influential predictors included ecosystem fire resistance; distance to roads, cities, and railroads; road density; mean October precipitation; elevation; median house value; and population density. Wildfires in the MTNF are caused overwhelmingly by arson, which, when combined with our results, suggests that arsonists may seek out flammable fuel types in remote areas with easy access. Within this general anthropogenic fire regime, we found a more subordinate effect of specific human variables (e.g., population density) on modern fire occurrence than did similar studies in the Upper Midwest, perhaps because our study area encompassed primarily federal forestlands with low population density.

scholarly journals MODELING URBAN CRIME PATTERNS USING SPATIAL SPACE TIME AND REGRESSION ANALYSIS

2019 ◽  
Vol XLII-4/W16 ◽  
pp. 247-254 ◽  
Author(s):  
H. Hashim ◽  
W. M. N. Wan Mohd ◽  
E. S. S. M. Sadek ◽  
K. M. Dimyati
Keyword(s):  
Population Density ◽  
Population Size ◽  
Hot Spot ◽  
Space Time ◽  
Urban Crime ◽  
Ols Regression ◽  
Crime Patterns ◽  
Factors Influencing ◽  
Size Population ◽  
Crime Pattern

Abstract. The population size, population density and rate of urbanization are often crediting to contributing increasing a crime pattern specially in city. Urbanism model stating that the rise in urban crime and social problems is based on three population indicators namely; size, density and heterogeneity. The objective of this paper is to identify crime patterns of the hot spot urban crime location and the factors influencing the crime pattern relationship with population size, population density and rate of urbanization population. This study employed the ArcGIS Pro 2.4 tool such as Emerging Hot Spot Analysis (Space Time) to determine a crime pattern and Ordinary Least Squares (OLS) Regression to determine the factors influencing the crime patterns. By using these analyses tools, this study found that 54 (53%) out of 102 total neighbourhood locations (2011–2017 years) had a 99 percent significance confidence level where z-score exceeded +2.58 with a small p-value (p < 0.01) as the hot spot crime location. The result of data analysis using OLS regression explains that combination of exploratory variable model rate of urbanization and population size contributes 56 percent (R2 = 0.559) variance in crime index rate incident [F (3,39) = 18.779, p < 0.01). While the population density (β = 0.045, t = 0.700, p > 0.10) is not a significance contributes to the change in crime index rate in Petaling and Klang district. The importance of the study is useful information for encouraging government and law enforcement agencies to promote safety and reduce risk of urban population crime areas.

Recolonisation by Rabbits (Oryctolagus Cuniculus) After Warren Ripping or Warren Fumigation.

1994 ◽  
Vol 16 (1) ◽  
pp. 51 ◽  
Author(s):  
I Parer ◽  
G Milkovits
Keyword(s):  
Population Density ◽  
Oryctolagus Cuniculus ◽  
First Year ◽  
Factors Influencing ◽  
Control Schemes ◽  
Group Control ◽  
Main Factors ◽  
Second Year ◽  
Main Factor

Attempts were made to exterminate rabbits at six separate sites; recolonisation was measured over the following two years. Three sites were treated by repeated warren ripping and three by repeated warren fumigation. At all sites the warren treatments were supplemented by shooting and dogging. Two years after treatment, the density of rabbits was 56% of the original density on fumigated sites and 50% on ripped sites. In the first year after treatment, reopened warrens were found more commonly than newly dug warrens; in the second year there were more new warrens than reopened ones. More of the treated warrens reopened on fumigated sites (40%) than on ripped sites (21%). For individual warrens, the number of entrances at treatment and the distance a warren was from untreated rabbit populations were the main factors influencing the probability of reopening. Population density on the periphery of the sites was the main factor influencing the rate of recolonisation of the sites and group control schemes are recommended to minimise recolonisation after control.

Estimating population density of the Formosan subterranean termite, Coptotermes formosanus(Isoptera: Rhinotermitidae) using the effective sampling area of in-ground monitoring stations

2004 ◽  
Vol 94 (1) ◽  
pp. 47-53 ◽  
Author(s):  
H. Puche ◽  
N.-Y. Su
Keyword(s):  
Population Density ◽  
Coptotermes Formosanus ◽  
Subterranean Termite ◽  
Broward County ◽  
Sampling Area ◽  
Release Point ◽  
Factors Influencing ◽  
Average Proportion ◽  
Ground Monitoring ◽  
Effective Sampling Area

AbstractThe effective sampling area of a monitoring station, α, was calculated for several Coptotermes formosanus Shiraki colonies in Broward County, Florida, USA. A simple mark–recapture protocol provided data on termite station catch within a foraging range of a colony. Average recapture probability was 0.005 close to the releae point (< 5 m) and declined to 0.0008 at a distance of 51 to 60 m. The relation between the log % termites recaptured was fitted with log distance, to determine P(x), the average proportion of captured termites that started at distance x from the release point. The effective sampling area was estimated by using P(x) and the equation, α 2 π∫{ x P(x)} dx. Integrating this equation, an average estimate α that ranged from 0.607 to 14.5 m2 was obtained. Factors influencing the variation of α among the colonies are discussed. The effective sampling area estimated should be taken as a reliable estimator that translates subterranean termite catches into termite population density.

FACTORS AFFECTING SPRUCE BUDWORM (CHORISTONEURA FUMIFERANA) (CLEM.) MATING AND MATING DISRUPTION WITH PHEROMONE IN THE LABORATORY

1986 ◽  
Vol 118 (8) ◽  
pp. 797-805 ◽  
Author(s):  
B.M. Ponder ◽  
L.R. Kipp ◽  
C. Bergh ◽  
G.C. Lonergan ◽  
W.D. Seabrook
Keyword(s):  
Sex Pheromone ◽  
Population Density ◽  
Mating Disruption ◽  
Choristoneura Fumiferana ◽  
Spruce Budworm ◽  
Test Duration ◽  
Moth Population ◽  
Factors Affecting ◽  
Factors Influencing ◽  
Pheromone Components

AbstractFactors influencing spruce budworm (Choristoneura fumiferana) mating and mating suppression in an enclosed environment in the laboratory were investigated to develop a quantitative assay suited to statistical analysis. Mating in the absence of the two major components of spruce budworm sex pheromone (control) was not affected by changes in moth population density nor by increasing the experimental duration from 20 to 44 h. The proportions mated increased with an increase in the male:female ratio to 1.5:1 and when the experimental duration was prolonged to 68 h. Using a population density, sex ratio combination of 15:10 (male:female) the proportions of mated females decreased with increasing source concentrations of the two major spruce budworm sex pheromone components (95:5 E/Z-11–14-tetradecenal). This effect was diminished with increases in the population density and with extended test duration. Mating in the presence of pheromone remained lower than controls over all durations tested.

scholarly journals UN SDGs Implementation Level in the Urban Sector in Korea: Focusing on a Framework Application Based on Relative Efficiency Theory

2021 ◽  
Author(s):  
Jonghoon Yoo ◽  
Minkyoung Choi ◽  
Byungseol Byun
Keyword(s):  
Population Density ◽  
Waste Management ◽  
Relative Efficiency ◽  
Republic Of Korea ◽  
Financial Independence ◽  
Factors Influencing ◽  
Administrative Area ◽  
Efficiency Theory ◽  
The Republic ◽  
Implementation Level

The purpose of this study was to evaluate the implementation level of urban Sustainable Development Goals (SDGs) in the Republic of Korea and to measure the extent of internal and external impacts on the implementation level. An evaluation framework was established based on relative efficiency theory, and the implementation level of urban SDGs at the local government unit in the Republic of Korea was examined by performing an analysis of each stage. First, in reference to the 2018 cross-section, the implementation level of target 11.2 (public transportation) was assessed as excellent across the country, compared with the implementation level of targets 11.5 (disaster safety), 11.6 (environment), and 11.7 (public space), which were assessed as needing improvement. Second, the factors positively impacting the implementation level of target 11.2 were urban population, GRDP, financial independence, urbanization area, and bus-only lanes, whereas the factors positively impacting the implementation level of target 11.5 were population density and GRDP. The positive factors influencing the implementation level of target 11.6 (air quality sector) were found to be GRDP, financial independence, administrative area, and renewable energy generation, whereas the effective factors of the implementation level of target 11.6 (waste management sector) were analyzed as GRDP, financial independence, and the population density of households in the waste management area. The positive factors influencing the implementation level of target 11.7 were GRDP, financial independence, administrative area, and green area.

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